Functional and Survival Outcomes of Patients following the Harrington Procedure for Complex Acetabular Metastatic Lesions
Bibliographic record
Abstract
BACKGROUND: The Harrington surgical technique makes it possible to manage complex, extensive bone lesions using pins and cement to consolidate bone for acetabular cup positioning. However, it may be associated with a high reoperation rate, and the functional results of this surgery are not precisely described in the literature. METHODS: In a monocentric retrospective study including all patients operated on using the Harrington procedure associated with THA between 2005 and 2020, we aimed to assess preoperative and postoperative function, reoperation-free survival, and overall survival. RESULTS: Functional improvement was significant for Parker scores (preoperative: 3.6 ± 2.0; 6-month follow-up: 6.6 ± 3.2; 12-month follow-up: 7.6 ± 2.1) and Musculoskeletal Tumor Society (MSTS) scores (preoperative: 31.1 ± 16.2%; 6-month follow-up: 67.7 ± 30.6%; 12-month follow-up: 82.4 ± 24.0%). Of the 21 patients included, the reoperation-free survival rate was 76.1% [CI 95%: 58.1-99.7] at six and twelve months, with the main complications being pin migration (50.0%) and infection (25%). The patient overall survival rate was 76.2% [95% CI: 59.9-96.7] at six months and 61.9% [95% CI: 59.9-96.7] at 12 months. DISCUSSION: These results underlined significant functional improvements following a conventional Harrington procedure, with acceptable reoperation rates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".